mlsanityData to 14 Oct 2026

AI in (and for) Games

arXiv 2105.03123 ↗First posted 7 May 2021cs.AI cs.HCcited by 0

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Abstract (arXiv)

This chapter outlines the relation between artificial intelligence (AI) / machine learning (ML) algorithms and digital games. This relation is two-fold: on one hand, AI/ML researchers can generate large, in-the-wild datasets of human affective activity, player behaviour (i.e. actions within the game world), commercial behaviour, interaction with graphical user interface elements or messaging with other players, while games can utilise intelligent algorithms to automate testing of game levels, generate content, develop intelligent and responsive non-player characters (NPCs) or predict and respond player behaviour across a wide variety of player cultures. In this work, we discuss some of the most common and widely accepted uses of AI/ML in games and how intelligent systems can benefit from those, elaborating on estimating player experience based on expressivity and performance, and on generating proper and interesting content for a language learning game.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 10 of its 77 references that are in the map. First posted on arXiv 7 May 2021.

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References · 10

  1. 2017Procedural Content Generation via Machine Learning (PCGML)cited by 137
  2. 2017STARDATA: A StarCraft AI Research Datasetcited by 7
  3. 2019Machine learning and semantic analysis of in-game chat for cyberbullyingcited by 7
  4. 2017Games and Big Data: A Scalable Multi-Dimensional Churn Prediction Modelcited by 3
  5. 2018Between an Arena and a Sports Bar: Online Chats of eSports Spectatorscited by 2
  6. 2021Developing for personalised learning: the long road from educational objectives to development and feedbackcited by 2
  7. 2018There is more to PCG than Meets the Eye: NPC AI, Dynamic Camera, PVS and Lightmapscited by 1
  8. 2019A Security Case Study for Blockchain Gamescited by 1
  9. 2020Open and Cultural Data Games for Learningcited by 1
  10. 2020Shimon the Robot Film Composer and DeepScore: An LSTM for Generation of Film Scores based on Visual Analysiscited by 1

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